class_docstr: A pytorch module that is a wrapper for FrozenCLIPEmbedder module. it enhances FrozenCLIPEmbedder, making it possible to
  have unlimited prompt length and assign weights to tokens in prompt.
docstr: returns the maximum number of tokens a prompt of a known length can have before it requires one more PromptChunk to be represented
docstr_tok: ["returns","the","maximum","number","of","tokens","a","prompt","of","a","known","length","can","have","before","it","requires","one","more","PromptChunk","to","be","represented"]
code: def get_target_prompt_token_count(self, token_count):
      """returns the maximum number of tokens a prompt of a known length can have before it requires one more PromptChunk to be represented"""
  
      return (
          math.ceil(max(token_count, 1) / self.chunk_length)
          * self.chunk_length
      )
  
imports: import math
  from collections import namedtuple
  import torch
  from modules import prompt_parser, devices, sd_hijack
  from modules.shared import opts
label_desc: Use image node_id 3 for calling the FrozenCLIPEmbedderWithCustomWordsBase obj's underlying member method code with example usage: obj.get_target_prompt_token_count(token_count) and returns: unknown